Predicting perimetric defects from en face maps of retinal nerve fibre layer reflectance

To develop criteria to predict visual hemifields with deep perimetric defects based on retinal nerve fibre layer (RNFL) reflectance, in a transparent process whose components can be assessed by independent laboratories analysing data from their own small groups.

The analysis was carried out in four stages, using three independent groups of patients-30, 33 and 62 participants-with glaucoma and age-similar controls. The first stage used Group 1 to develop a criterion for RNFL reflectance images at 24, 36 or 48 μm below the inner limiting membrane (ILM). The second stage evaluated the criterion using Group 2. The third stage developed a second criterion to improve performance for Groups 1 and 2 combined. The fourth stage evaluated the second criterion with Group 3. Confidence intervals for sensitivity and specificity were then computed by combining results from all three groups.

The first criterion identified all hemifields with deep defects and no hemifields from controls, using a within-eye reference for healthy RNFL. For Group 2, specificity remained high but sensitivity was reduced. The second criterion improved sensitivity by using location-specific reference values. For Group 3, sensitivity remained high but reduced specificity was found. Confidence intervals showed substantial overlap for the two criteria.

We developed two criteria to identify patients with deep perimetric defects with high specificity and sensitivity. Several improvements are warranted: automated identification of the fovea-disc angle and optic disc locations, evaluation of normal variation in patterns of RNFL thickness, improved segmentation of ILM and major vasculature, reduction of within-eye variability in RNFL reflectance of healthy eyes, assessment of effects of image quality, assessment of effects of comorbidity and effectiveness of other devices.